Summary: Translation and Scale­Invariant Gesture Recognition in
Complex Scenes
Alexandra Stefan 1 , Vassilis Athitsos 2 , Jonathan Alon 1 , and Stan Sclaroff 1
1 Computer Science Department, Boston University
2 Computer Science and Engineering Department, University of Texas at Arlington
ABSTRACT
Gestures are a natural means of communication between humans,
and also a natural modality for human­computer interaction. Auto­
matic recognition of gestures using computer vision is an important
task in many real­world applications, such as sign language recog­
nition, computer games control, virtual reality, intelligent homes,
and assistive environments. In order for a gesture recognition sys­
tem to be robust and deployable in non­laboratory settings, the sys­
tem needs to be able to operate in complex scenes, with compli­
cated backgrounds and multiple moving and skin­colored objects.
In this paper we propose an approach for improving gesture recog­
nition performance in such complex environments. The key idea
is to integrate a face detection module into the gesture recognition
system, and use the face location and size to make gesture recog­
nition invariant to scale and translation. Our experiments demon­